Public Health Priorities

Highlights

Early Warning, Alert and Response

• Completeness for weekly reporting was 41% for the non-conflict affected states and 81% for the IDP sites.

• 18 new suspect measles cases reported from five states. One new suspect measles case reported in Malakal PoC.

• 45 cases including 10 deaths of suspect VHF reported in Aweil North and Aweil West Counties with 24 December 2015 as the earliest date of onset. Sample testing is underway.

• ABD cases have increased in all sectors of Bentiu PoC.

• Pneumonia and TB/HIV/AIDS were the most common causes of mortality during the reporting week.

System performance

Special focus on measles • No new confirmed measles outbreaks in the week. Table 4.1

shows counties with confirmed measles outbreaks in 2016.

• This week, 18 new suspect measles cases reported from eight counties in five states with most cases reported from Aweil West county (Table 4.1). One suspect measles case reported in Malakal PoC

• Vaccination currently underway in Twic and plans are underway to conduct vaccination in Aweil West, Aweil South, one payam in Aweil Center (Nyalat); and 4 payams in Aweil East (Baak; Marial Bai; Mangok; and Mangal Tong II).

Completeness for weekly reporting was 41% for the non-conflict affected states and 81% for the IDP sites (Table 1).

Lakes state exceeded the target completeness reporting rate of 80% (Figures 1c and 2).

Timeliness for weekly reporting remains very low (18-69%) for both the non-conflict affected states and IDP sites (Table 1).

Cumulative completeness reporting rate for 2016 was 44% for the non-conflict affected states and 94% for the IDP sites (Table 1).

Table 1 | Surveillance performance in South Sudan as of W13 2016

Republic of South SudanW13| 28 Mar – 3 Apr 2016

Weekly Epidemiological BulletinIntegrated Disease Surveillance and Response (IDSR)

Active alerts:

Meningitis

Suspect VHF

Suspect cholera

!

!

Active responses

MeaslesHepatitis E Virus

Suspect VHF

SystemTotal

FacilitiesTimelines Completeness Timeliness Completeness

inweek 13of2016 Cumulative for2016IDSR 1392 251(18%) 574(41%) 382(27%) 611(44%)EWARN 48 33(69%) 39(81%) 33(69%) 45(94%)

Figure 1c | IDSR Surveillance performance in South Sudan as of W13 2016

Completeness for weekly reporting in the nonconflict affected states remains low and is largely attributed to: a) insecurity in parts of Western Equatoria and Western Bahr el Ghazal; b) to closure of facilities after the departure of HPF supported staff in states like Northern Bahr el Ghazal where up to 26 HF have closed; and Mingkaman in Lakes and; c) due to the current administrative transition at state level.

Event based surveillance W13 of 2016

• Data missing

12%

2%

27%

0.009%

59%

Figure1a|IDSRProportionalmorbidityWK132016

AWD

ABD

Malaria

Measles

Others

19%

5% 7%

90%

18%

53%42%

67%78% 79%

0% 5% 7% 5% 0%42% 42%

24%

54%

0%0%

20%

40%

60%

80%

100%

CES EES Jonglei Lakes NBeG Unity UNS WBeG WES Warrap

HealthFacilitiesreporting[%]

Figure 2|IDSRweekly reporting bystate WK132016

Completeness Timeleness Target

1% 16%

26%

14%1%

42%

Figure1b|ProportionalmorbidityinIDPsW132016

Measles

Malaria

ARI

AWD

ABD

Other

IDSR and EWARN Reporting Performance by Partner and County in 2016

Trends for top causes of Morbidity

17 (33%) hospitals, 128 (39%) PHCCs, and 429 (42%) PHCUs in 32 counties of the nonconflict-affected states submitted their IDSR reports (Table 2).

A total of 15 counties in the nonconflict-affected states did not submit any report in the reporting week (Table 2).

9 partner-supported health facilities in the conflict-affected states did not submit their reports in the reporting week (Table 2).

!

Table 2 | Reporting Performance [Timeliness and Completeness] by Partner and County as of W13 2016

Figure 6b | EWARN Priority Disease Proportionate Morbidity W52 2013 to W13 2016

System DiseaseNewcases W13 Cumulative casesas at W13 of2015 2016 2015 2016

IDSR

Malaria 26,871 18,290 377,924 323,194AWD 10,706 7,722 119,720 94,128Meningitis 2 0 17 13ABD 2,175 1,453 26,384 19,515Measles 6 6 98 232AJS 1 1 8 6

EWARN

Malaria 3,285 3,315 33,966 73,397AWD 2,467 2,835 21,155 36,469ARI 3,500 5,187 38,014 77,430ABD 283 305 2,484 2,767Measles 16 112 88 288AJS 2 28 46 368Meningitis 0 0 5 7

Table 4 | Top causes of morbidity in 2015 and 2016

Figure 6a | IDSR priority disease morbidity trends W1 2015 to W13 2016

Overall morbidity trends for 2014-2016

The 9 health facilities in the IDPs that did not submit their reports in week 12 are supported by HLSS, IMA, IMC, IRC, and World Relief (Table 2).

The best performing facilities since the beginning of 2016 are supported by IOM, IMC, UNIDO, and UNKEA while those that really need to improve are facilities supported by COSV, IMA, IRC, MedAir, GOAL, and CCM (Table 2).

Table 3 shows the total consultations in 2016.

No.IDSR

Silent Counties W13 2016

1 Yei

2 Kajokeji

3 Lainya

4 Morobo

5 Terekeka

6 Aweil West

7 Ikotos

8 KapoetaNorth

9 Lofan

10 Torit

11 Aweil Center

12 Aweil East

13 KapoetaSouth

14 Magwi

15 Budi

ARI is the top cause of morbidity in the IDPs while malaria leads in the nonconflict affected states (Figures 1a, 1b, 6a, 6b, Table 4).

Consultations Table 3 | Consultations in South Sudan as of W13 2016

SurveillanceSystem

Consultations in week13of2016 Cumulative consultations for2016

<5years ≥5years Total <5years ≥5years Total

IDSR 20,011 31,480 51,491 299,466 481,676 781,142

EWARN 20,322 336,290

Total 71,813 1,117,432

0

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casesper100,000population

Epidemiological weekof reporting in2015

Completeness ABD Malaria Measles AWD

Partner Number ofhealth facilities

W132016

Completeness Timeliness

# # % # %

CCM 0 0 0% 0 0%

COSV 1 1 100% 1 100%

GOAL 2 2 100% 0 0%

HLSS 3 0 0% 0 0%

IMA 5 4 80% 5 100%

IMC 8 7 88% 6 75%

IOM 6 6 100% 6 100%

IRC 4 2 50% 2 50%

Medair 2 2 100% 2 100%

MSF-E 3 0 0% 0 0%

MSF-H 5 5 100% 3 60%

SMC 5 5 100% 5 100%

UNIDO 3 3 100% 3 100%

UNKEA 2 2 100% 0 0%

World Relief 2 0 0% 0 0%

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2013

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-02-22

2015

-09-20

Percentageofallconsultations

%_Malaria %_ARI %_Measles

Malaria

Acute Respiratory Infection (ARI)

Figure 11b shows ARI morbidity by IDP site in week 13 of 2016.

Status: Urgent

!

Malaria

Malaria

Malaria is a common cause of mor bidity and accounted for27% and 16% of the consultati ons i n the nonconflict- affec tedstates and ID P si tes respectively (Fig. 1a, 1b, 7, 8, 9, 10a,10b).

This w eek m al aria i nci dence i n Warrap and W estern Bar elGhazal; Benti u PoC and M alakal PoC is within the expec tedlevels (Fig. 8, 9, 10a, 10b).

In the w eek , tw o m alaria deaths wer e reported from AweilNorth and Akobo (Tables 5, 6).

In the IDPs, ARI registered the highest proportionate morbidity of 25.5% as compared to 16.3% in week 13 of 2015 and 23.9% in week 12 of 2016 (Fig. 11).

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Figure7|IDSRmalaria trendsbyweek,2014 - 2016

2014 2015 2016

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casesper100,000

Epidemiological Week

Figure8|IDSRtrends formalaria inWarrap, Wk01 toWk13, 2016

2016 Thirdquartile 2012-2014

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casesper1

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Epidemiological week

Figure 9|Malaria Incidence forWestern BharelGhazal,week 01to13,2016

2016 Third quartile2012-2014

252

-

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800

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casesper10,000

Weekof reporting

Figure10b |Malariatrendfor IDPsinMalakalPoC2014to2016

incidence 2014 incidence 2015Third quartile incidence 2016

-

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800

1,000

1 3 5 7 9 11 13 15 17 19 21 23 25 27 29 31 33 35 37 39 41 43 45 47 49 51 53

casesper10,000

Weekof reporting

Figure 10a|Malaria trend for IDPsinBentiu PoC2014 to2016

incidence 2014 incidence 2015Third quartile incidence 2016

0%

5%

10%

15%

20%

25%

30%

35%

40%

45%

01 03 05 07 09 11 13 15 17 19 21 23 25 27 29 31 33 35 37 39 41 43 45 47 49 51 53

Percentoftotalconsultations

Epidemiological weekof reporting

Figure11|ARItrendsinIDPsW512013toW132016

2014 2015 2016

0%10%20%30%40%50%60%70%

IMCClinic2

IOMSector3PH

CCMSF-HTho

nyorClinic

UNIDO

MajakPH

CUSM

CMalo

uMSF-HLankien

PHCC

MSF-HBentiu

PoC

Hospital

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oHo

spital

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MeerMob

ileC

linic

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GOALDetho

maCamp2

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GOALKoradarIDPclinic

IMCClinic1

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MSF-HLeerHo

spital

IOMAbayokClinic

IOMSector1PH

CCIOMW

onthow

Mob

ileClinic

IMAWauShillukIDP…

IOMPayerC

linic

IMALulM

obileClinic

IOMClinic

COSVJiechPH

CUUN

IDO

Gand

orPHC

UIMAOgod

Mob

ileClinic

IRCSector5Clinic

SMCPaktapM

obileClinic

Percentofallconsultatio

ns

Figure11b|ARI Incidenceby IDPSite inW132016

Acute bloody diarrhoea (ABD)

Acute bloody diarrhoea (ABD)

!

Acute watery diarrhoea (AWD)

Acute watery diarrhoea (AWD)

AWD is a common cause of morbidity that currently accounts for 12% and 14% consultations in the nonconflict-affected states and IDP sites respectively (Fig. 1a, 1b).

The overall AWD incidence [cases per 100,000] in the reporting week was 63 in the non-conflict affected states with Unity (107), Lakes (81), Upper Nile (142), and Western Bahr el Ghazal (149) being the most affected (Fig. 12).

In the IDPs, AWD morbidity is higher when compared to the corresponding period of 2014 and 2015 (Fig. 13).

Figure 14 shows AWD morbidity by IDP site in week 13 of 2016.

ABD is a common cause of morbidity that currently accounts for 2% and 1% of consultations in the non-conflict affected states and IDP sites respectively (Fig. 1a, 1b).

The overall ABD incidence [cases per 100,000] in the reporting week was 12 in the non-conflict affected states with Lakes (24), Warrap (24), Western Bahr el Ghazal (23), and Upper Nile (22) being the most affected (Fig. 15).

Among the IDPs, the current ABD burden is lower when compared to 2014 but higher than in 2015 (Fig. 16 and 17).

Figure 17 shows the number of ABD cases by IDP clinic in week 13 of 2016. ABD cases have increased in all sectors of Bentiu PoC and are being investigated.

0

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120

1 3 5 7 9 11 13 15 17 19 21 23 25 27 29 31 33 35 37 39 41 43 45 47 49 51 53

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Figure 12| IDSRAWDtrends byweek,2014 - 2016

2014 2015 2016

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Casesper10

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Figure15|IDSRABD trendbyweek,2013 - 2016

2014 2015 2016

0%

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15%

20%

25%

30%

35%

40%

01 03 05 07 09 11 13 15 17 19 21 23 25 27 29 31 33 35 37 39 41 43 45 47 49 51 53

Percentofallconsultations

Figure13|AWDtrendsinIDPsW512013toW132016

2014 2015 2016

0%10%20%30%40%50%60%70%

MSF-HLeerHo

spital

MedairAbayokClinic

IMCClinic1

MedairW

onthow

Clinic

MSF-HTho

nyorClinic

IMCSite1

UNKEAJikmirPH

CCIMCERPoC

1SM

CDo

rokM

obileClinic

UNIDO

MajakPH

CUUN

IDO

Gand

orPHC

UUN

KEAMandengP

HCC

MSF-HLankien

PHCC

UNIDO

MeerMob

ileC

linic

IMAKo

dokM

obileClinic

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oHo

spital

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PoC

Hospital

SMCAyuelditMob

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maCamp2

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SMCMalo

uCO

SVJiechPH

CUIMAOgod

Mob

ileClinic

SMCPadietMob

ileC

linic

Percentofallconsultations

Figure14|ARI Incidenceby IDPSite inW132016

0%

1%

2%

3%

4%

5%

6%

7%

010305070911131517192123252729313335373941434547495153

Percentofallconsultatio

ns

Figure16|ABD trends in IDPsW512013 to W132016

2014 2015 2016

0%

5%

10%

15%

20%

25%

MedairAbayokClinic

MedairW

onthow

…UN

KEAMandeng…

GOALKoradarIDP…

UNIDO

MeerMob

ile…

UNKEAJikmirPH

CCMSF-HBentiu

PoC

…IMAKo

dokM

obile…

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nyorClinic

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CPadietMob

ile…

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spital

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IOMPayerC

linic

IOMAbayokClinic

IMAWauShillukIDP…

IOMClinic

IOMSector3PH

CCIOMSector1PH

CCIOMW

onthow

…IMCClinic3

Percentofallconsultations

Figure 17|ABDIncidencebyIDPSiteinW132016

!

Nutrition In the reference period (Jan- March 2016) theoverall nutrition situation re mains very critical inUnity, with Global Acute Malnutrit ion (GAM)rates reaching and exceeding 30%.

Bentiu PoC (hosting 120,278 of displacedmainly fro m Central and Southern Unitycounties), and Mayom county showed GAMrates of 34.1% and 30% respectively.

In other counties in Unity, GAM rates were above theemergency threshold, with peaks reaching 26.5%.

IPC analysis updates (Jan-Mar 2016)http://www.ipcinfo.org/ipcinfo-detail-forms/ ipcinfo-map-detail/en/c/379480/

GAM rates at critical levels (GAM=15.0-29.9%) havealso been regis tered in Upper Nile, Jong lei, Warrap,Northern Bahr el Ghazal and some parts of EasternEquatoria.

Deteriorating scenario is also emerging in Lakes. An estimated 2.8 million people are currently facing acute food insecurity (period: Jan - March 2016).

The nutrition situation is likely to remain very critical in Unity and critical in most parts of Greater Upper Nile, NBeG, and Warrap, throughout the approaching lean season.

Mayendit North

In week 5 and 6, Medair completed a rapid MUACassessment in Mayendit North, Un ity andconfirmed suspected emergency levels of acutemalnutrition.

MUAC screening of children 6- 59 months andpregnant and lactating women (PLW) conducted in5 locations: Dablual, Tutnyang (Luom), Jaguar,Thaker and Rubkwai.

A total of 2,969 children and 1,146 PLW werescreened. Results showed proxy GAM rate above

the emergency threshold in:• Luom: proxy GAM 17.7% with associated SAM

6.1%• Rubkwai: proxy GAM 26.9% with associated

SAM 12.9%• Dablual: proxy GAM 16.0% with associated

SAM 6.4%

In the same locations of Luom, Rubkwai andDablual, proxy GAM for PLW was also found to behigh (23.0%, 28.7% and 15.1% respectively).Findings confirmed the October 2015 IPC results,which classified Mayendit County population’snutritional status as ‘very critical’ (GAM ≥30%).

Figure 17a | Updated IPC classification for South Sudan, January to March 2016

!

Measles

Measles

No new counties with confirmed measles outbreaks.

This week, 18 new suspect measles cases were reported from 8 counties in five states with most cases reported from Aweil West county (Table 4). One new suspect measles case reported in Malakal PoC.

A cumulative of 52 measles IgM positive cases confirmed in 2016 (Table 4.1).

Vaccination currently underway in Twic and plans are underway to conduct vaccination in Aweil West, Aweil South, one payam in Aweil Center (Nyalat); and 4 payams in Aweil East (Baak; Marial Bai; Mangok; and Mangal Tong II).

Figures 18.1 – 18.4 show the measles epidemic curves for Twic, Abyei, Mayom, and Rubkona.

Measles

Measles outbreaks confirmed in eight counties (Table 4.1)

Table4.1|Measles cases bylocation andstatus asatW13of 2016

Tables 4.1 to 4.4 show the distribution of measles cases age distribution in Rubkona, Twic, and Aweil West.

State County NewsuspectcasesW13,2016

Suspectcases in2016

ConfirmedCasesin2016

Samples testedin2016

Outbreakstatus in2016

CES Mangatain IDP 2 2 2 ConfirmedCES UN House PoC 4 3 3 ConfirmedCES Juba 9 AlertCES Yei 7 0 0 AlertEES Magwi 8 7 AlertLakes Rumbek Center 4 2 4 AlertLakes Yirol East 1 0 AlertLakes YirolWest 3 10 AlertNBG AweilWest 5 76 8 5 ConfirmedNBG Aweil Center 1 0 0 AlertNBG Aweil East 1 6 0 0 AlertNBG Aweil South 1 16 0 2 AlertNBG Aweil North 6 0 0 AlertUnity Abiemnhom 1 1 0 AlertUnity Mayendit 27 2 12 ConfirmedUnity Mayom 2 164 9 12 ConfirmedUnity Leer (Adok) 7 2 6 ConfirmedUnity Rubkona 4 66 3 4 ConfirmedUNS Maban 1 1 1 AlertWarrap Abyei 171 8 16 ConfirmedWarrap Gogrial East 1 AlertWarrap GogrialWest 9 1 3 AlertWarrap Twic 1 45 11 11 ConfirmedWBG Wau 8 0 1 AlertWES Ibba 2 0 2 AlertWES Tambura 4 0 4 AlertWES Yambio 9 0 7 AlertUNS Malakal PoC 1 1 0 0 AlertTotal 18 666 52 102

Table 4.1|Suspectmeasles casedistributioninRubkona

Agein yrs Female Male Total cases Percentage [%] Cum.%

<1year 8 3 11 16.7 16.7

1-4yrs 24 21 45 68.2 84.8

5-9yrs 4 5 9 13.6 98.5

10-14yrs 1 1 1.5 100

Total 37 29 66 100

Table4.2|Suspectmeasles casedistribution inTwic

Agein yrs Female Males Total cases Percentage [%] Cum.%

<1yrs 2 2 4 9.1 9.1

1-4yrs 11 10 21 47.7 56.8

5-9yrs 7 1 8 18.2 75.0

10-14years 1 2 3 6.8 81.8

15+yrs 2 6 8 18.2 100

Total cases 23 21 44 100

Table4.3|Suspectmeasles casedistribution inAweil West

Agein yrs Female Male Total cases Percentage [%] Cum.%

<1year 6 8 22 28.9 28.9

1-4yrs 10 7 25 32.9 61.8

5-9yrs 8 6 25 32.9 94.7

10-14yrs 1 2 2.6 97.4

15+yrs 1 1 2 2.6 100

Total cases 25 23 76 100

0

4

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12

16

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24

50 51 52 53 1 2 3 4 5 6 7 8 9 10 11 12 13

2015 2016

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Figure18.4|Measlescases,Rubkona,W522015toW132016

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Fig.18.3Measlescases,Mayom,W532015toW122016

Alive Died

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2015 2016Num

berofcases

Fig.18.2Measlescases,Abyei,W522015toW122016

Alive Died

0

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15

2 3 4 5 6 7 8 9 10 11 12

numberofcases

weekof rashonset in2016

Fig.18.1|Measlescases,Twic,W52015toW122016

Alive Died

!

Suspect meningitis

Hepatitis E Virus (HEV)

No new suspect measles case reported in Nyong Payam in Torit.

Since 5 January 2016, eight suspect cases of meningitis have been reported from Torit in Eastern Equatoria (Figure 18.4).

Nyong Payam in Torit county is the most affected after reporting 7 (100%) suspect cases.

Four samples tested at the National Public Health Laboratory (NPHL) were negative for bacterial meningitis.

The weekly attack rates for Nyong Payam remain below the alert and action threshold for epidemic meningitis .

HEV is the commonest cause of acute jaundice syndrome1 with cases confirmed in Mingkaman, Bentiu, Lankien, Guit, and Leer.

Bentiu PoC/Town reported 32 new HEV cases in the reporting week (Fig. 19). Since the beginning of 2016, a total of 351 HEV cases have been reported from Bentiu.

Since the beginning of the crisis, 2,598 HEV cases including 19 deaths (CFR 0.73%) reported in Bentiu; 158 cases including seven deaths (CFR 4.4%) in Mingkaman; 38 cases including one death (CFR 2.6%) in Lankien; 3 confirmed HEV cases in Melut; 3 HEV confirmed cases in Guit; and 1 HEV confirmed case in Leer.

HEV transmission is currently reported in Bentiu PoC and Bentiu Town and is largely propagated by the sub-optimal access to safe water and sanitation.

Other diseases of public health importanceAcute Flaccid Paralysis | Suspected Polio

During 2016, a cumulative of 59 AFP cases have been reported countrywide (three new AFP cases in week 13 of 2016).

In 2016, the annualized non-Polio AFP (N PAFP) rate (cases per100,000 population chil dren 0-14 years) is 2.7 per 100,000population of childr en 0-14 years ( tar get ≥2 per 100,000 childr en 0-14 years).

Eight s tates (Eastern Equatoria, Wes tern Equatoria, W ester n Bahrel Ghazal, Northern Bahr el Ghazal, Jongl ei, Lakes, Warr ap, andUpper Nile) have attai ned the targeted NPAFP r ate of ≥2 per100,000 children 0- 14 years i n 2016. The non- Poli o Enter ovirus(NPEV) isolation rate (a m easur e of the quality of the specim encold chain) is 11% in 2016 (target ≥10%).

Stool adequacy was 92% in 2016, a rate that is higher than the target of ≥80%.

Guinea Worm | Dracunculiasis

No reported cases.

Visceral Leishmaniasis | Kala-azar

In 2016, a total of 238 cases [198 (83.2%) new; 35 (14.7 %)relapses; 5 (2.1%) PKDL] including 14 death (CFR 5.9%) and 1(0.7%) defaulter were reported from 21 treatment centers (17 newcases including 3 deaths from 5 health facilities in week 12, 2016).

During the corresponding period in 2015, a total of1,222 casesincluding 39 deaths (CFR 2.7%) and 39 (2.7%) defaulters werereported from 21 treatment centers.

Of the 238 cases reported in 2016, the majority were from Lankien(135) followed by Ulang (20), Melut IDP (35), Maiwut (5), Walgak (3),Wau Shiluk (7), Malakal IDP (5), Bentiu PoC (3), and Yuai (7), whileKoradar IDP reported one case.

The most affected groups included male [150 cases (63%)], thoseaged ≥15years [144 cases (47.9%]) and those aged 5-14years [87(36.6%). Children under five years were less affected [37 cases(15.5%)].

Viral Haemorrhagic Fever45 suspect VHF cases including 10 deaths (CFR 22%) reported fromAweil with 24 December 2015 as the earliest date of onset.

Children are most afffected and account fot most cases and deaths

Most common case symptoms include: unexplained bleeding(epistaxis and vomiting coffee grounds), fever, fatigue, vomiting,jaundice

There is no evidence of person-to-person transmission. Vector borneVHF suspected.

A total of 57 samples shipped for testing in WHO collaboratingcenters. Preliminary testing at UVRI and NICD was negative forEbola, Marburg, Crimean-Congo Hemorrhagic Fever, and Rift ValleyFever. Arboviral testing is underway.

Animal bites | Suspected rabies

No new suspect cases reported.

1 Thisonlyapplies tothecurrentcontext of SouthSudan

Cholera | Suspected

A suspect cholera case involving a 5 year old boy from Malual Chat (military barracks) in Bor was reported by Bor State Hospital on 15 March 2016. RDT was negative for cholera (sample sent for culture). Investigations by RRT revealed no additional cases. Cultiuring was negative for cholera.

0

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50 51 52 53 1 2 3 4 5 6 7 8 9 10 11 12 13

2015 2016

Num

berofcases

Figure18.4|Suspectmeningitiscases,Torit,EESW532015toW132016

Alive Died

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02468

10121416

3 7 1115192327313539434751 3 7 1115192327313539434751 2 6 10

2014 2015 2016

No.casesinBentiu

No,casesinothersites

Epidemiological week

Figure 19|HEVtrends inMingkaman, Bentiu &LankienW102014 toW132016

Awerial Lankien Bentiu

Mortality

Crude and under five mortality rates in IDPs

Overall mortality in 2016

A total of seven deaths were reported from the stable areas with three deaths attributed to acute watery diarrhoea, malaria, and acute jaundice syndrome (Table 5).

Among the IDPs, Akobo, Bentiu PoC, Juba 3, Wau Shiluk, Melut, and Malakal PoC submitted mortality data (Table 6).

This week, 28 deaths were reported including 14 (50%) in Bentiu PoC and 10 (36%) in children <5 years (Table 6).

This week, pneumonia and TB/HIV/AIDS had the highest proportionate mortality among the IDPs (Table 6).

The U5MR in all the IDP sites that submitted mortality data in week 13 of 2016 were below the emergency threshold of 2 deaths per 10,000 per day (Fig. 20).

Note: Mortality rates are calculated for PoC sites only and are based on the latest available population data from OCHA. They are reported from line lists and should include community and facility-based deaths. However, due to rapid in/out migration from the PoC sites, and possible under-reporting of community-level deaths, they should be interpreted carefully.

!

Table 6 | Proportional mortality by cause of death in IDPs W12 2016Table 5 | Mortality from IDSR reports countrywide W12 2016

Since the beginning of 2016, a total 400 deaths have been reported from the IDP sites of which 137 (34%) were children under-5 years (Table 7).

Most of deaths occurred in Bentiu, Malakal and Juba 3 PoC (Table 7).

Since the beginning of 2016, TB/HIV/AIDS has registered the highest proportionate mortality of 11.5% (Table 7).

During 2016, commonest causes of death in U5s were severe malaria, severe pneumonia, medical complications of malnutrition, and perinatal complications.

The Crude Mortality Rates [CMR] in all the IDP sites that submitted mortality data in week 13 of 2016 were below the emergency threshold of 1 death per 10,000 per day (Fig. 21).

The other causes of mortality in the week included septicaemia, and medical complications of acute malnutrition.

Table 7 | Mortality by IDP site and cause of death W1 to W13 2016

STATE COUNTYAWD≥5yrs AJS<5yrs

Malaria<5yrs Others

Totaldeaths<5yrs

Totaldeaths≥5yrs

LAKES RumbekCentre 1 0 0 0 0 1

NBGZ Aweil North0 0 1 0 1 0

UNITY Abiemnhom0 1 0 0 1 0

WBGZ JurRiver0 0 0 1 1 0

WRP TonjNorth0 0 0 1 1 0

WRP TonjSouth0 0 0 2 1 1

Total deaths 1 1 1 4 5 2

Cause ofDeathbyIDPsite

Akobo Bentiu Juba3 Malakal Wau ShilukGrandTotal

Proportionatemortality

[%]<5yrs <5yrs ≥5yrs <5yrs ≥5yrs <5yrs ≥5yrs <5yrs ≥5yrsAcutewaterydiarrhoea 1 1 4

Asthma 1 1 4Chronic illness 1 1 4HeartFailure 1 1 4LiverDisease 1 1 2 7Malaria 1 1 4Meningitis 1 1 4Perinatal death 1 1 4Pneumonia 2 1 3 11SAM 1 1 2 7Septicemia 2 1 3 11SevereAnaemia 1 1 4TB/HIV/AIDS 1 1 1 1 4 14Unknown 3 3 11COPD 1 1 4Unknown Cause 1 1 4Hepatitis BInfection 1 1 4

Grand Total 1 6 8 1 6 1 3 1 1 28 100

0.0

0.5

1.0

1.5

2.0

2.5

1 3 5 7 9 11131517192123252729313335373941434547495153 2 4 6 8 1012

2015 2016

deathsper10,000perday

Epidemiological week

Figure20|EWARNU5MRbySite- W12015toW13of2016

Bentiu Juba3 Malakal Mingkaman

Melut Akobo WauShiluk Threshold

0.0

0.2

0.4

0.6

0.8

1.0

1.2

1 3 5 7 9 11 13 15 17 19 21 23 25 27 29 31 33 35 37 39 41 43 45 47 49 51 53 2 4 6 8 10 12

2015 2016

deathsper10,000perday

Epidemiological week

Figure21|EWARNCrudeMortalityRateforW12015toW13of2016

Bentiu Juba3 Malakal MingkamanMelut Akobo WauShiluk Threshold

IDPsite Acutewatery

diarrhoea

Cancer

HeartFailure

Hypertension

Kala-Azar

Malaria

Measles

Perinataldeath

Pneumonia

SAM

Septicem

ia

TB/H

IV/A

IDS

GSW

Meningitis

Maternaldeath

Others

GrandTotal

Bentiu 7 4 17 1 4 14 13 25 1 1 126 213

Juba3 1 1 1 1 3 5 2 3 13 26 56

Malakal 1 1 2 1 3 4 4 1 2 4 45 68Melut 2 1 1 2 2 2 2 5 17

Akobo 3 1 10 1 3 1 12 31

WauShiluk 1 2 4 8 15Grand Total 12 1 8 2 1 31 2 11 30 21 4 46 6 1 2 222 400

Proportionatemortality [%] 3.0 0.3 2.0 0.5 0.3 7.8 0.5 2.8 7.5 5.3 1.0 11.5 1.5 0.3 0.5 55.5 100

Data sources

Editorial

Acknowledgements

This bulletin presents disease trends from the Integrated Disease Surveillance and Response (IDSR) System and the Early Warning Alert and Disease Network (EWARN).

The respective data is submitted by public health facilities serving host communities (non-conflict affected states or non IDP sites) and partner-supported facilities serving internally displaced persons (IDP) in the Republic of South Sudan.

MoH and WHO gratefully acknowledge the support of all MoH staff in the states, WHO Field Officers, and implementing-health cluster partners in collecting and reporting the data used in this bulletin.

Contact

For more information, please contact: Department of Epidemics, Preparedness and ResponseMoH Republic of South Sudan

Email: outbreak_22_2010@yahoo.com

Outbreak toll-free line:1144

This bulletin is produced by the Ministry of Health with technical support from the WHO

Editorial: Dr.Thomas A.Ujjiga, Dr.AliceL.Igale,Dr.GeorgeW.Worri, Korsuk Scopus, RobertM.Lasu, Rose A.Dagama, JanePita,Louis Julu,GabrielWaat,MarinaAdrianopoli, Dr.Lincoln Charimari, Dr.AllanM.Mpairwe,Dr.JosephF.Wamala, Dr.JohnP.Rumunu

Supported by the Global EWARS project | info@ewars.ws